import sys
import os
import logging
import re
import json
from typing import Dict, List, Any, Optional, Tuple

# 添加项目根路径到 sys.path
sys.path.append(os.path.join(os.path.dirname(os.path.abspath(__file__)), '..', '..'))

# 导入 MySQLUtil
from shared.utils.MySQLUtil import MySQLUtil

# 设置日志
logger = logging.getLogger(__name__)

def get_离职次数分布(
    project_id: int,
    questionnaire_ids: List[int],
    product_code: Optional[str] = None,
    project_code: Optional[str] = None,
    region_code: Optional[str] = None,
    education: Optional[str] = None
) -> Dict[str, Any]:
    """
    离职次数分布 - 指标计算函数
    
    ## 指标说明
    计算毕业生正式参加工作后的离职次数分布情况，统计各选项选择人数的占比，
    其中离职率是统计后三项(1次、2次、3次及以上)的合计占比。
    指标数据来源于指定项目的毕业生短期问卷调研数据。
    
    ## Args
        project_id (int): 项目ID，用于查询项目配置信息
        questionnaire_ids (List[int]): 问卷ID集合，用于确定数据范围
        product_code (Optional[str]): 产品编码，用于路由到特定计算逻辑
        project_code (Optional[str]): 项目编码，用于路由到特定计算逻辑
        region_code (Optional[str]): 区域编码，用于路由到特定计算逻辑
        education (Optional[str]): 学历筛选条件，可选值：[本科毕业生，专科毕业生，硕士研究生，博士研究生]
        
    ## 示例
    ### 输入
    ```json
    {
        "project_id": 5895,
        "questionnaire_ids": [11158, 11159]
    }
    ```
    
    ### 输出
    ```json
    {
        "success": true,
        "message": "ok",
        "code": 0,
        "result": {
            "0次": 0.45,
            "1次": 0.3,
            "2次": 0.15,
            "3次及以上": 0.1,
            "离职率": 0.55
        }
    }
    ```
    """
    logger.info(f"开始计算指标: 离职次数分布, 项目ID: {project_id}")
    
    try:
        db = MySQLUtil()  

        # 1. 查询项目配置信息
        project_sql = """
        SELECT client_code, item_year, dy_target_items, split_tb_paper 
        FROM client_item 
        WHERE id = %s
        """
        project_info = db.fetchone(project_sql, (project_id,))
        if not project_info:
            raise ValueError(f"未找到项目ID={project_id}的配置信息")

        client_code = project_info['client_code']
        item_year = project_info['item_year']
        split_tb_paper = project_info['split_tb_paper']
        
        logger.info(f"项目配置: client_code={client_code}, item_year={item_year}, split_tb_paper={split_tb_paper}")

        # 2. 计算 shard_tb_key
        shard_tb_key = re.sub(r'^[A-Za-z]*0*', '', client_code)
        logger.info(f"计算得到 shard_tb_key: {shard_tb_key}")

        # 3. 查询问卷信息
        questionnaire_sql = f"""
        SELECT id, dy_target 
        FROM wt_template_customer 
        WHERE id IN ({','.join(['%s'] * len(questionnaire_ids))})
        """
        questionnaires = db.fetchall(questionnaire_sql, tuple(questionnaire_ids))
        if not questionnaires:
            raise ValueError(f"未找到问卷ID集合={questionnaire_ids}的配置信息")
        
        logger.info(f"查询到问卷信息: {questionnaires}")

        # 4. 过滤特定调研对象的问卷
        valid_questionnaire_ids = [q['id'] for q in questionnaires if q['dy_target'] == 'GRADUATE_SHORT']
        if not valid_questionnaire_ids:
            raise ValueError("未找到目标调研对象(GRADUATE_SHORT)的问卷ID")
            
        logger.info(f"找到有效问卷ID: {valid_questionnaire_ids}")

        # 5. 查询问题信息
        question_sql = """
        SELECT id, wt_code, wt_obj 
        FROM wt_template_question_customer 
        WHERE cd_template_id = %s AND wt_code = 'T00000385' AND is_del = 0
        """
        question_info = db.fetchone(question_sql, (valid_questionnaire_ids[0],))
        if not question_info:
            raise ValueError("未找到问题编码T00000385的问题信息")
            
        logger.info(f"找到问题信息: {question_info['id']}")

        # 6. 解析问题选项
        wt_obj = json.loads(question_info['wt_obj'])
        if not wt_obj or 'itemList' not in wt_obj:
            raise ValueError("问题选项配置信息有误")
        
        options = {item['key']: item['val'] for item in wt_obj['itemList']}
        logger.info(f"问题选项: {options}")

        # 7. 构建动态表名
        answer_table = f"re_dy_paper_answer_{split_tb_paper}"
        student_table = f"dim_client_target_baseinfo_student_{item_year}"

        # 8. 构建SQL查询条件
        education_condition = ""
        if education:
            education_condition = f"AND s.education = '{education}'"
        
        # 9. 执行查询计算各选项占比
        sql = f"""
        SELECT
            SUM(CASE WHEN t1.c1 = 1 THEN 1 ELSE 0 END) as count_0,
            SUM(CASE WHEN t1.c2 = 1 THEN 1 ELSE 0 END) as count_1,
            SUM(CASE WHEN t1.c3 = 1 THEN 1 ELSE 0 END) as count_2,
            SUM(CASE WHEN t1.c4 = 1 THEN 1 ELSE 0 END) as count_3_plus
        FROM {answer_table} t1
        JOIN {student_table} s ON t1.target_no = s.target_no
        WHERE
            t1.cd_template_id = %s
            AND t1.wid = %s
            AND t1.ans_true = 1
            AND s.shard_tb_key = %s
            AND s.item_year = %s
            {education_condition}
        """
        params = (valid_questionnaire_ids[0], question_info['id'], shard_tb_key, item_year)
        result = db.fetchone(sql, params)
        
        if not result:
            raise ValueError("未找到有效的答案数据")

        total = sum([result['count_0'], result['count_1'], result['count_2'], result['count_3_plus']])
        if total == 0:
            raise ValueError("答案数据总量为0")

        # 10. 计算各选项占比
        ratio_0 = round(result['count_0'] / total, 4)
        ratio_1 = round(result['count_1'] / total, 4)
        ratio_2 = round(result['count_2'] / total, 4)
        ratio_3_plus = round(result['count_3_plus'] / total, 4)
        leave_ratio = round(ratio_1 + ratio_2 + ratio_3_plus, 4)

        logger.info(f"指标 '离职次数分布' 计算成功")
        return {
            "success": True,
            "message": "ok",
            "code": 0,
            "result": {
                "0次": ratio_0,
                "1次": ratio_1,
                "2次": ratio_2,
                "3次及以上": ratio_3_plus,
                "离职率": leave_ratio
            }
        }

    except Exception as e:
        logger.error(f"计算指标 '离职次数分布' 时发生错误: {str(e)}", exc_info=True)
        return {
            "success": False,
            "message": f"数据获取失败: 离职次数分布",
            "code": 500,
            "error": str(e)
        }